Systems and methods for improving haul road conditions

ABSTRACT

A method for improving haul road surface conditions comprises collecting performance data associated with at least one machine operating on a haul route and determining a rolling resistance of each of the at least one machine based on the performance data. An average rolling resistance associated with one or more portions of the haul route is determined based on the rolling resistance of each of the at least one machine. The one or more portions of the haul route are identified as irregular if the average rolling resistance of the one or more portions exceeds a threshold resistance value. A proposed modification to the irregular portion of the haul route is generated, and performance of the at least one machine is simulated based on the proposed modification. The method also includes outputting results of the simulated performance.

TECHNICAL FIELD

The present disclosure relates generally to the operations andmanagement of haul routes and, more particularly, to systems and methodsfor improving haul road conditions.

BACKGROUND

In many work environments, particularly those that employ a fleet ofmachines that cooperate to perform a common task, productivity,efficiency, and profitability of the work environment may be dependentupon a variety of interrelated factors. For example, in mineenvironments that employ heavy equipment to excavate and transportmaterials from a mine site to a production facility, the productivity ofthe mine is directly dependent upon the health and productivity of eachmachine in the fleet. For certain types of machines, such as transportvehicles and haulers, machine productivity may also depend on workenvironment conditions (e.g., terrain conditions, weather conditions,etc.), as these conditions often affect speed, handling, and traction ofthe machines.

Early detection of structural defects in the haul road is imperative tothe successful maintenance of haul road operations, as the weight of themachines and large volume of traffic associated with the haul road maycause even minor structural defects to degrade the haul road surfacequite rapidly. In order to detect structural defects in the haul road,many conventional work environments implement haul road monitoring andmaintenance programs. These haul road monitoring and maintenanceprograms involve rudimentary defect detection techniques, such as visualinspections, test-drive inspections, and as-needed emergency inspections(based, for example, on machine operator reports). In addition to beingtime consuming and inconvenient, these manual methods are oftenunreliable for detecting haul road deficiencies. For instance, visualinspection techniques may be susceptible to human error, as subsurfacedefects and other problems that may not be visible may go undetected.Test-drive inspections, while somewhat more reliable than visualinspections, are often not effective in simulating traffic and loadingconditions that the haul route undergoes during normal operations, asthese tests often prescribe shutting down the haul road duringperformance of the test. Emergency inspections based on machine operatorreports typically only detect haul road deficiencies after they havemanifested themselves, which is often too late for implementingpreventative maintenance procedures. Thus, in order to effectivelydetect and correct haul road deficiencies in a timely manner, anautomated system for identifying haul road deficiencies and determiningcorrective actions to resolve these deficiencies may be required.

One conventional method for efficiently identifying changes in haul roadconditions without relying on time-intensive manual inspectiontechniques is described in U.S. Pat. No. 5,817,936 (“the '936 patent”)to Schricker. The '936 patent describes a method for detecting a changein the condition of a road by sensing a plurality of parameters from oneor more machines traveling along the road. The sensed parameters may beused to calculate a resistance factor for each of the one or moremachines and determine an average resistance factor for the fleet ofmachines. If the average resistance factor exceeds a threshold level, achange (i.e., deficiency or fault) in the road segment may be identifiedand/or corrected.

Although some conventional methods, such as the method described in the'936 patent, may enable detection of changes in road conditions based onperformance of a fleet of machines, they may be limited in certainsituations. For example, while these conventional systems may be capableof detecting changes in haul road conditions, they may not be equippedto analyze prospective solutions that correct or otherwise address thesechanges in haul road conditions. As a result, mine operators and/or workenvironment managers may be required to make haul road repairs and/ormodifications without a complete understanding of the impact of therepairs and/or modifications on the performance, budget, and/orlong-term health of the haul route and/or one or more machinesassociated therewith.

Moreover, many conventional methods for detecting changes in haul roadconditions, like the one described in the '936 patent, may not beintegrated with performance modeling and simulation software that allowsusers to make modifications to certain machine or haul road parametersand test these modifications before implementation in the workenvironment. As a result, conventional systems may be limited totrial-and-error methods for haul road improvement, where haul roadimprovements are implemented and the impact of these improvements aredetermined in subsequent haul road operations. If required, adjustmentsmay be made in order to incrementally improve haul route performanceuntil a desired performance goal in achieved. Although thesetrial-and-error methods can be effective, they methods are often timeconsuming and costly, particularly if several iterations of themodification/test process are required. Thus, in order to effectivelyand reliably improve haul road conditions while controlling costs, asystem and method for identifying problematic haul road conditions andtesting one or more proposed haul road improvement options prior toimplementation may be required.

The presently disclosed systems and methods for improving haul routeconditions are directed toward overcoming one or more of the problemsset forth above.

SUMMARY

In accordance with one aspect, the present disclosure is directed towarda method for improving haul road surface conditions. The method maycomprise collecting performance data associated with at least onemachine operating on a haul route and determining a rolling resistanceof each of the at least one machine based on the performance data. Anaverage rolling resistance may be determined based on the rollingresistance of each of the at least one machine. A portion of the haulroute may be identified as irregular if the average rolling resistanceof the at least one machine exceeds a threshold resistance value. Aproposed modification to the irregular portion of the haul route may begenerated, and a performance of the at least one machine may besimulated based on the proposed modification. The method may alsoinclude outputting results of the simulated performance of the at leastone machine.

According to another aspect, the present disclosure is directed toward amethod for improving haul road surface conditions. The method maycomprise collecting performance data associated with at least onemachine operating on a haul route and monitoring, based on theperformance data, a number of gear changes of each of the at least onemachine. An average number of gear changes may be determined based onthe number of gear changes for each of the at least one machine. One ormore portions of the haul route may be identified as irregular if theaverage number of gear changes exceeds a threshold limit. A proposedmodification to one or more irregular portions of the haul route may begenerated and performance of the at least one machine may be simulatedbased on the proposed modification. The results of the simulatedperformance may be output.

In accordance with yet another aspect, the present disclosure isdirected toward a haul route management system. The system may include acondition monitoring system in data communication with a machineoperating in a work environment and configured to collect performancedata associated with at least one machine. The system may also include atorque estimator communicatively coupled to the condition monitoringsystem and configured to determine a rolling resistance of each of theat least one machine based on the performance data. The system mayfurther include a performance simulator communicatively coupled to thetorque estimator and the condition monitoring system. The performancesimulator may be configured to determine an average rolling resistancebased on the rolling resistance of each of the at least one machine. Theperformance simulator may also be configured to identify a portion ofthe haul route as irregular if the average rolling resistance of the atleast one machine exceeds a threshold resistance value. The performancesimulator may be further configured to receive a proposed modificationto the irregular portion of the haul route, simulate a performance ofthe at least one machine based on the proposed modification, and outputresults of the simulated performance.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an exemplary work environment consistent with thedisclosed embodiments;

FIG. 2 provides a schematic diagram illustrating certain componentsassociated with the work environment of FIG. 1;

FIG. 3 provides a flowchart depicting one exemplary method for improvinghaul road surface conditions, consistent with certain disclosedembodiments; and

FIG. 4 provides a flowchart depicting another exemplary method forimproving haul road surface conditions, consistent with certaindisclosed embodiments.

DETAILED DESCRIPTION

FIG. 1 illustrates an exemplary work environment 100 consistent with thedisclosed embodiments. Work environment 100 may include systems anddevices that cooperate to perform a commercial or industrial task, suchas mining, construction, energy exploration and/or generation,manufacturing, transportation, agriculture, or any task associated withother types of industries. According to the exemplary embodimentillustrated in FIG. 1, work environment 100 may include a miningenvironment that comprises one or more machines 120 a, 120 b coupled toa haul route management system 135 via a communication network 130. Workenvironment 100 may be configured to monitor, collect, and filterinformation associated with the status, health, and performance of oneor more machines 120 a, 120 b, and distribute the information to one ormore back-end systems or entities, such as haul route management system135 and/or subscribers 170. It is contemplated that additional and/ordifferent components than those listed above may be included in workenvironment 100.

As illustrated in FIG. 1, machines 120 a, 120 b may include one or moreexcavators 120 a and one or more transport machines 120 b. Excavators120 a may embody any machine that is configured to remove material fromthe mine and load the material onto one or more transport machines 120b. Non-limiting examples of excavators 120 a include, for example,bucket-type excavating machines, electromagnetic-lift devices, backhoeloaders, dozers, etc. Transport machines 120 b may embody any machinethat is configured to transport materials within work environment 100such as, for example, articulated trucks, dump trucks, or any othertruck adapted to transport materials. The number, sizes, and types ofmachines illustrated in FIG. 1 are exemplary only and not intended to belimiting. Accordingly, it is contemplated that work environment 100 mayinclude additional, fewer, and/or different components than those listedabove. For example, work environment 100 may include a skid-steerloader, a track-type tractor, material transfer vehicle, or any othersuitable fixed or mobile machine that may contribute to the operation ofwork environment 100.

In one embodiment, each of machines 120 a, 120 b may include on-boarddata collection and communication equipment to monitor, collect, and/ordistribute information associated with one or more components ofmachines 120 a, 120 b. As shown in FIG. 2, machines 120 a, 120 b mayeach include, among other things, one or more monitoring devices 121,such as sensors or electronic control modules coupled to one or moredata collectors 125 via communication lines 122; one or more transceiverdevices 126; and/or any other components for monitoring, collecting, andcommunicating information associated with the operation of machines 120a, 120 b. Each of machines 120 a, 120 b may also be configured toreceive information, warning signals, operator instructions, or othermessages or commands from off-board systems, such as a haul routemanagement system 135. The components described above are exemplary andnot intended to be limiting. Accordingly, the disclosed embodimentscontemplate each of machines 120 a, 120 b including additional and/ordifferent components than those listed above.

Monitoring devices 121 may include any device for collecting performancedata associated with one or more machines 120 a, 120 b. For example,monitoring devices 121 may include one or more sensors for measuring anoperational parameter such as engine and/or machine speed and/orlocation; fluid pressure, flow rate, temperature, contamination level,and or viscosity of a fluid; electric current and/or voltage levels;fluid (i.e., fuel, oil, etc.) consumption rates; loading levels (i.e.,payload value, percent of maximum payload limit, payload history,payload distribution, etc.); transmission output ratio, slip, etc.; haulgrade and traction data; drive axle torque; intervals between scheduledor performed maintenance and/or repair operations; and any otheroperational parameter of machines 120 a, 120 b.

In one embodiment, transport machines 120 b may each include at leastone torque sensor 121 a for monitoring a torque applied to the driveaxle. Alternatively, torque sensor 121 a may be configured to monitor aparameter from which torque on the drive axle may be calculated orderived. It is contemplated that one or more monitoring devices 121 maybe configured to monitor certain environmental features associated withwork environment 100. For example, one or more machines 120 a, 120 b mayinclude an inclinometer for measuring an actual grade associated with asurface upon which the machine is traveling. It is also contemplatedthat one or more monitoring devices 121 may be dedicated to thecollection of machine location data. For example, machines 120 a, 120 bmay each include GPS equipment for monitoring location data (e.g.,latitude, longitude, elevation, etc.) associated with the machine.

Data collector 125 may be configured to receive, collect, package,and/or distribute performance data collected by monitoring devices 121.Performance data, as the term is used herein, refers to any type of dataindicative of at least one operational aspect associated with one ormore machines 120 or any of its constituent components or subsystems.Non-limiting examples of performance data may include, for example,health information such as fuel level, oil pressure, engine temperature,coolant flow rate, coolant temperature, tire pressure, or any other dataindicative of the health of one or more components or subsystems ofmachines 120 a, 120 b. Alternatively and/or additionally, performancedata may include status information such as engine power status (e.g.,engine running, idle, off), engine hours, engine speed, machinegroundspeed, machine location and elevation, current gear that themachine is operating in, or any other data indicative of a status ofmachine 120. Optionally, performance data may also include certainproductivity information such as task progress information, load vs.capacity ratio, shift duration, haul statistics (weight, payload, etc.),fuel efficiency, or any other data indicative of a productivity ofmachine 120. Alternatively and/or additionally, performance data mayinclude control signals for controlling one or more aspects orcomponents of machines 120 a, 120 b. Data collector 125 may receiveperformance data from one or more monitoring devices via communicationlines 122 during operations of the machine.

According to one embodiment, data collector 125 may automaticallytransmit the received data to haul route management system 135 viacommunication network 130. Alternatively or additionally, data collector125 may store the received data in memory for a predetermined timeperiod, for later transmission to haul route management system 135. Forexample, if a communication channel between the machine and haul routemanagement system 135 becomes temporarily unavailable, the performancedata may be retrieved for subsequent transmission when the communicationchannel has been restored.

Communication network 130 may include any network that provides two-waycommunication between machines 120 a, 120 b and an off-board system,such as haul route management system 135. For example, communicationnetwork 130 may communicatively couple machines 120 a, 120 b to haulroute management system 135 across a wireless networking platform suchas, for example, a satellite communication system. Alternatively and/oradditionally, communication network 130 may include one or morebroadband communication platforms appropriate for communicativelycoupling one or more machines 120 a, 120 b to haul route managementsystem 135 such as, for example, cellular, Bluetooth, microwave,point-to-point wireless, point-to-multipoint wireless,multipoint-to-multipoint wireless, or any other appropriatecommunication platform for networking a number of components. Althoughcommunication network 130 is illustrated as a satellite wirelesscommunication network, it is contemplated that communication network 130may include wireline networks such as, for example, Ethernet, fiberoptic, waveguide, or any other type of wired communication network.

Haul route management system 135 may include one or more hardwarecomponents and/or software applications that cooperate to improveperformance of a haul route by monitoring, analyzing, optimizing, and/orcontrolling performance or operation of one or more individual machines.Haul route management system 135 may include a condition monitoringsystem 140 for collecting, distributing, analyzing, and/or otherwisemanaging performance data collected from machines 120 a, 120 b. Haulroute management system 135 may also include a torque estimator 150 fordetermining a drive axle torque, estimating a total effective grade,calculating a rolling resistance, and/or determining other appropriatecharacteristics that may be indicative of the performance of a machineor machine drive train. Haul route management system 135 may alsoinclude a performance simulator 160 for simulating performance-basedmodels of machines operating within work environment 100 and adjustingoperating parameters of machines 120 a, 120 b and/or physical featuresof the haul route to improve work environment productivity.

Condition monitoring system 140 may include any computing systemconfigured to receive, analyze, transmit, and/or distribute performancedata associated with machines 120 a, 120 b. Condition monitoring system140 may be communicatively coupled to one or more machines 120 viacommunication network 130. Condition monitoring system 140 may embody acentralized server and/or database adapted to collect and disseminateperformance data associated with each of machines 120 a, 120 b. Oncecollected, condition monitoring system 140 may categorize and/or filterthe performance data according to data type, priority, etc. In the caseof critical or high-priority data, condition monitoring system 140 maybe configured to transmit “emergency” or “critical” messages to one ormore work site personnel (e.g., repair technician, project managers,etc.) identifying machines that have experienced a critical event. Forexample, should a machine become disabled, enter an unauthorized workarea, or experience a critical engine operation condition, conditionmonitoring system 140 may transmit a message (text message, email, page,etc.) to a project manager, job-site foreman, shift manager, machineoperator, and/or repair technician, indicating a potential problem withthe machine.

Condition monitoring system 140 may include hardware and/or softwarecomponents that perform processes consistent with certain disclosedembodiments. For example, as illustrated in FIG. 2, condition monitoringsystem 140 may include one or more transceiver devices 126; a centralprocessing unit (CPU) 141; a communication interface 142; one or morecomputer-readable memory devices, including storage device 143, a randomaccess memory (RAM) module 144, and a read-only memory (ROM) module 145;a display unit 147; and/or an input device 148. The components describedabove are exemplary and not intended to be limiting. It is contemplatedthat condition monitoring system 140 may include alternative and/oradditional components than those listed above.

CPU 141 may be one or more processors that execute instructions andprocess data to perform one or more processes consistent with certaindisclosed embodiments. For instance, CPU 141 may execute software thatenables condition monitoring system 140 to request and/or receiveperformance data from data collector 125 of machines 120 a, 120 b. CPU141 may also execute software that stores collected performance data instorage device 143. In addition, CPU 141 may execute software thatenables condition monitoring system 140 to analyze performance datacollected from one or more machines 120 a, 120 b, perform diagnosticand/or prognostic analysis to identify potential problems with themachine, notify a machine operator or subscriber 170 of any potentialproblems, and/or provide customized operation analysis reports,including recommendations for improving machine performance.

CPU 141 may be connected to a common information bus 146 that may beconfigured to provide a communication medium between one or morecomponents associated with condition monitoring system 140. For example,common information bus 146 may include one or more components forcommunicating information to a plurality of devices. CPU 141 may executesequences of computer program instructions stored in computer-readablemedium devices such as, for example, a storage device 143, RAM 144,and/or ROM 145 to perform methods consistent with certain disclosedembodiments, as will be described below.

Communication interface 142 may include one or more elements configuredfor two-way data communication between condition monitoring system 140and remote systems (e.g., machines 120 a, 120 b) via transceiver device126. For example, communication interface 142 may include one or moremodulators, demodulators, multiplexers, demultiplexers, networkcommunication devices, wireless devices, antennas, modems, or any otherdevices configured to support a two-way communication interface betweencondition monitoring system 140 and remote systems or components.

One or more computer-readable medium devices may include storage devices143, a RAM 144, ROM 145, and/or any other magnetic, electronic, flash,or optical data computer-readable medium devices configured to storeinformation, instructions, and/or program code used by CPU 141 ofcondition monitoring system 140. Storage devices 143 may includemagnetic hard-drives, optical disc drives, floppy drives, flash drives,or any other such information storing device. A random access memory(RAM) device 144 may include any dynamic storage device for storinginformation and instructions by CPU 141. RAM 144 also may be used forstoring temporary variables or other intermediate information duringexecution of instructions to be executed by CPU 141. During operation,some or all portions of an operating system (not shown) may be loadedinto RAM 144. In addition, a read only memory (ROM) device 145 mayinclude any static storage device for storing information andinstructions by CPU 141.

Condition monitoring system 140 may be configured to analyze performancedata associated with each of machines 120 a, 120 b. According to oneembodiment, condition monitoring system 140 may include diagnosticsoftware for analyzing performance data associated with one or moremachines 120 a, 120 b based on threshold levels (which may be factoryset, manufacturer recommended, and/or user configured) associated with arespective machine. For example, diagnostic software associated withcondition monitoring system 140 may compare an engine temperaturemeasurement received from a particular machine with a predeterminedthreshold engine temperature. If the measured engine temperature exceedsthe threshold temperature, condition monitoring system 140 may generatean alarm and notify one or more of the machine operator, job-sitemanager, repair technician, dispatcher, or any other appropriate personor entity.

In accordance with another embodiment, condition monitoring system 140may be configured to monitor and analyze productivity associated withone or more of machines 120 a, 120 b. For example, condition monitoringsystem 140 may include productivity software for analyzing performancedata associated with one or more machines 120 a, 120 b based onuser-defined productivity thresholds associated with a respectivemachine. Productivity software may be configured to monitor theproductivity level associated with each of machines 120 a, 120 b andgenerate a productivity report for a project manager, a machineoperator, a repair technician, or any other entity that may subscribe tooperator or machine productivity data (e.g., a human resourcesdepartment, an operator training and certification division, etc.)According to one exemplary embodiment, productivity software may comparea productivity level associated with a machine (e.g., amount of materialmoved by a particular machine) with a predetermined productivity quotaestablished for the respective machine. If the productivity level isless than the predetermined quota, a productivity notification may begenerated and provided to the machine operator and/or project manager,indicating the productivity deficiency of the machine.

Condition monitoring system 140 may be in data communication with one ormore other back-end systems and may be configured to distribute certainperformance data to these systems for further analysis. For example,condition monitoring system 140 may be communicatively coupled to atorque estimator 150 and may be configured to provide performance dataassociated with the machine drive axle to torque estimator 150.Alternatively or additionally, condition monitoring system 140 may be indata communication with a performance simulator 160 and may beconfigured to provide performance data to performance simulator 160 forfurther analysis. Although torque estimator 150 and performancesimulator 160 are illustrated as standalone systems that are external tocondition monitoring system 140, it is contemplated that one or both oftorque estimator 150 and performance simulator 160 may be included as asubsystem of condition monitoring system 140.

Torque estimator 150 may include a hardware or software moduleconfigured to receive/collect certain performance data from conditionmonitoring system 140 and determine, based on the received operationdata, a drive axle torque associated with one or more machines 120 a,120 b. Torque estimator 150 may be configured to determine a drive axletorque based on performance data collected by torque sensor 121 a.Alternatively or additionally, drive axle torque may be estimated basedon the performance data and the known design parameters of the machine.For example, based on an engine operating speed and the operating gear,torque estimator 150 may access an electronic look-up table and estimatethe drive axle torque of the machine at a particular payload weightusing the look-up table.

Once an estimated machine drive axle torque is determined, torqueestimator 150 may estimate a total effective grade for the one or moremachines. For example, torque estimator 150 may estimate a totaleffective grade (TEG) value as:

${TEG} = {\frac{RP}{GMW} - \frac{MA}{AG}}$

where RP refers to machine rimpull, GMW refers to gross machine weight,MA refers to the acceleration of the machine, and AG refers to theactual grade of the terrain on which that machine is located. Grossmachine weight and machine acceleration may be monitored using on-boarddata monitoring devices 121. Actual grade may be estimated based onmonitored GPS data associated with the machine. For example, actualgrade may be determined using based on latitude, longitude, andelevation of the machine derived from precision GPS data gathered fromon-board GPS equipment. According to one embodiment, actual grade may bedetermined by calculating ratio between the vertical change in position(based on the elevation data associated with the GPS data) and thehorizontal change in position (based on the latitude and longitude dataassociated with the GPS data). Alternatively or additionally, actualgrade may be calculated using an on-board data monitoring device suchas, for example, an inclinometer. Rimpull may be determined as:

${RP} = \frac{{DAT} \times {LPTR} \times {PTE}}{TDRR}$

where DAT refers to the torque applied to the machine drive axle, LPTRrefers to the lower power train reduction factor, PTE refers to theefficiency of the power train, and TDRR refers to the dynamic rollingradius of the tire. Lower power train reduction may be determined bymonitoring a change in gear during real-time calculation of rim pull.Power train efficiency may be calculated based on real-time performancedata collected from the machine. Tire dynamic rolling radius may beestimated based on a monitored tire pressure, speed, and gross machineweight.

Once total effective grade has been determined, torque estimator 150 maydetermine a rolling resistance associated with one or more of machines120 a, 120 b. A rolling resistance value may be calculated as:

RR=TEG−(AG+EL)

where EL refers to the efficiency loss of the machine. Efficiency lossmay be estimated as the difference between input power efficiency andoutput power efficiency, which may be estimated based on empirical testdata at particular engine operating speeds and loading conditions. Asexplained, actual grade may be determined based on calculationsassociated with collected GPA data and/or monitored using an on-boardinclinometer.

Performance simulator 160 may be configured to simulate performance ofmachines 120 a, 120 b under various operational or environmentalconditions. Based on the simulation results, performance simulator 160may determine one or more operating conditions to achieve a desiredperformance of machines 120 a, 120 b and/or work environment 100.

Performance simulator 160 may be any type of computing system thatincludes component or machine simulating software. The simulatingsoftware may be configured to build an analytical model corresponding toa machine or any of its constituent components based on empirical datacollected from real-time operations of the machine. Once the model isbuilt, performance simulator 160 may analyze the model under specificoperating conditions (e.g., load conditions, environmental conditions,terrain conditions, haul route design conditions, etc.) and generatesimulated performance data of the machine based on the specifiedconditions.

According to one embodiment, performance simulator 160 may include idealdesign models associated with each of machines 120 a, 120 b. These idealmodels can be electronically simulated to generate ideal performancedata (i.e., data based on the performance of the machine as designed(under ideal operating conditions)). Those skilled in the art willrecognize that, as a machine ages, components associated with themachine may begin to exhibit non-ideal behavior, due to normal wear,stress, and/or damage to the machine during operation. In order toprovide more realistic performance simulations consistent with thesenon-idealities, the ideal models may be edited based on actualperformance data collected from machines 120 a, 120 b, thus creatingactual or empirical models of a respective machine and/or its individualcomponents.

Performance simulator 160 may simulate the actual models to predictperformance and productivity of the machine under a variety of operatingconditions. For example, performance simulator 160 may simulate anactual model of hauler 120 b under a machine operating and/or haul routesurface conditions to determine a speed, torque output, enginecondition, fuel consumption rate, greenhouse gas emission level, haulroute completion time, etc. associated with each simulated condition. Inone embodiment, performance simulator 160 may be configured to simulatethe actual model of hauler 120 b under a variety of physical conditions(e.g., grade levels, friction levels, smoothness, density, hardness,moisture content, etc.) associated with the haul route surface todetermine how changes or improvements to the haul route design impactthe performance of hauler 120 b.

According to one exemplary embodiment, one or more of conditionmonitoring system 140 and/or performance simulator 160 may be configuredto monitor trends in performance data associated with portions of thehaul route. For example, performance simulator 160 may be configured tomonitor real-time total effective grade associated with one or moremachines operating on a haul route. Using precision GPS data,performance simulator 160 may associate the real-time total effectivegrade data with a particular position of the machine when the totaleffective grade data was collected. Performance simulator 160 may beconfigured to identify trends in the monitored total effective gradedata and correlate these trends with a particular portion of the haulroute in order to identify potential problems with the haul route thatmay unnecessarily limit the performance of one or more machines.

According to another exemplary embodiment, performance simulator 160 maybe configured to detect performance deficiencies associated with one ormore machines 120 a, 120 b due to haul road conditions by determiningwhen machines 120 a, 120 b perform an excessive number of gear changesduring haul route operations. Performance simulator 160 may beconfigured to monitor and record the number of gear changes (e.g.,downshifts, upshifts, etc.) associated with one or more machines 120 a,120 b corresponding with particular portions of the haul route.Performance simulator 160 may be configured to calculate an averagenumber of gear changes associated with one or more haul route segments.Performance simulator 160 may identify segments of the haul route havingan average number of gear changes that exceeds a threshold acceptablelevel for further performance simulation and/or analysis.

According to yet another embodiment, performance simulator 160 and/orcondition monitoring system 140 may be configured to detectirregularities in a portion of the haul road based on differences inactual grade data associated with machines 120 a, 120 b. For example,performance simulator may be configured to monitor real-time actualgrade data associated with each machine, based on GPS data collectedfrom machines 120 a, 120 b. Performance simulator 160 may be configuredto determine the average actual grade for each segment of the haul roadand monitor trends in the average actual grade. Performance simulator160 may be configured to detect changes in the trends of the actualgrade data and monitor changes to identify potential problems with thehaul road. For instance, if the average actual grade of a particularsegment of the haul road is exhibiting a decreasing trend, performancesimulator 160 may associate this decrease with excessive haul road wear,and order an inspection of the segment in order to identify a cause ofthe decrease.

In addition to identifying particular haul route segments that may causeperformance problems associated with one or more machines, performancesimulator 160 may be configured to simulate machine models in order todetermine one or more solutions for correcting deficiencies associatedwith the particular haul route segments. For example, if the averagetotal effective grade of machines traveling over a haul route segmentexceeds a threshold level, performance simulator 160 may simulateperformance of one or more machines or machine types using modified haulroute parameters. According to one embodiment, performance simulator 160may adjust, for example, a surface parameter associated with the segment(e.g., grade, density, friction, etc.) and simulate performance of themachine at the adjusted surface parameter.

Performance simulator 160 may also include a diagnostic and/orprognostic simulation tool that simulates actual machine models (i.e.,models derived or created from actual machine data) to predict acomponent failure and/or estimate the remaining lifespan of a particularcomponent or subsystem of the machine. For example, based on performancedata associated with the engine and/or transmission, performancesimulator 160 may predict the remaining lifespan of the engine, drivetrain, differential, or other components or subsystems of the machine.Accordingly, performance simulator 160 may predict how changes in one ormore haul road parameters may affect the lifespan of one or more ofthese components. For instance, performance simulator 160 may estimatethat, if the grade of a particular haul road segment is reduced by 1.5%,thereby reducing the strain on the engine, transmission, and/or drivetrain, the remaining lifespan of the drive train may increase by 15%.Performance simulator 160 may periodically report this data to a mineoperator, project manager, machine operator, and/or maintenancedepartment of work environment 100.

Performance simulator 160 may be configured to output results of theperformance simulation(s). For example, performance simulator 160 mayoutput simulated performance data via display 147 of conditionmonitoring system 140. Alternatively and/or additionally, performancesimulator 160 may generate a haul road modification report 165associated with work environment 100. Haul route modification report 165may include performance simulation results corresponding to proposedmodifications to machine operating parameters and/or haul routeadjustment parameters. Alternatively or additionally, haul routemodification reports 165 may include paper-based or electronic reportsthat list one or more haul route segments associated with unacceptablemachine performance and/or recommended modifications to the one or morehaul route segments that may improve machine performance associated withthese segments.

Performance simulator 160 may be configured to distribute haul routemodification report(s) 165 to one or more subscribers 170 of haul routemodification data. Subscribers 170 may include, for example, projectmanagers, mine owners, repair technicians, shift managers, humanresource personnel, or any other person or entity that may be designatedto receive haul route modification reports 165.

It is contemplated that one or more of condition monitoring system 140,torque estimator 150, and/or performance simulator 160 may be includedas a single, integrated software package or hardware system.Alternatively or additionally, these systems may embody separatestandalone modules configured to interact or cooperate to facilitateoperation of one or more of the other systems. For example, while torqueestimator 150 is illustrated and described as a standalone system,separate from performance simulator 160, it is contemplated that torqueestimator 150 may be included as a software module configured to operateon the same computer system as performance simulator 160.

Processes and methods consistent with the disclosed embodiments mayprovide a solution for identifying haul road surface deficiencies basedon monitored performance data associated with one or more machinesoperating on the haul route. Specifically, the features and methodsdescribed herein allow project managers, equipment owners, and/or mineoperators to identify segments of a haul route that may cause aplurality of machines to operate inefficiently. Additionally, processesand features consistent with the disclosed embodiments may providerecommendations for adjusting and/or modifying haul road parametersassociated with underperforming segments of the haul route, simulatingperformance of the machine based on the recommendations, and providingthe simulated performance results to a subscriber. FIGS. 3 and 4 provideflowcharts 300 and 400, respectively, which illustrate exemplary methodsfor improving haul road surface conditions in work environments based onmachine performance data.

As illustrated in FIG. 3, performance data may be collected from atleast one machine operating on the haul route (Step 310). For example,condition monitoring system 140 of haul route management system 135 mayreceive/collect performance data from each machine operating in workenvironment 100. According to one embodiment, condition monitoringsystem 140 may automatically receive this data from data collectors 125associated with each of machines 120 a, 120 b. Alternatively oradditionally, condition monitoring system 140 may provide a data requestto each of machines 120 a, 120 b and receive performance data from eachmachine in response to the request.

Once performance data has been collected, a rolling resistanceassociated with each of the at least one machine may bedetermined/calculated based on the performance data associated with arespective machine (Step 320). For example, torque estimator 150 maydetermine the drive axle torque based on data received from torquesensor 121 a. Alternatively, torque estimator 150 may determine driveaxle torque using electronic look-up tables (compiled from empiricaltest data associated with the type and model of machine) based on engineoperating conditions, gear selection, and other data received from themachine. Once drive axle torque has been determined/estimated, torqueestimator 150 may calculate/estimate a total effective grade associatedwith each machine. Torque estimator 150 may determine a machine rollingresistance based on the total effective grade, actual grade of the haulroute, and efficiency loss of the machine.

According to one embodiment, rolling resistance values may becontinuously determined/calculated during machine operations on the haulroute. For example, as condition monitoring system 140 continuouslycollects performance data from one or more machines, torque estimator150 may calculate rolling resistance values corresponding with each setof collected performance data. Each rolling resistance value may betagged with a timestamp and location information (e.g., GPS data)corresponding to the time and location of the machine when theperformance data set was collected. By associating rolling resistancevalues with position data, performance simulator 160 can monitor trendsin rolling resistance values and correlate these trends with aparticular haul route segment.

Based on rolling resistance values associated with the individualmachines, an average machine rolling resistance for one or more haulroute segments may be determined (Step 330). For example, performancesimulator 160 may average previously stored rolling resistance dataassociated with a haul route segment with current rolling resistancedata for the segment.

Performance simulator 160 may compare the average rolling resistanceassociated with a haul route segment with a threshold resistance valuefor the segment (Step 340). If the average rolling resistance does notexceed a threshold resistance value (Step 340: No), indicating that theparticular haul route segment is operating normally, the process mayproceed back to Step 310 to continue monitoring performance data. Thethreshold resistance value may be defined by a haul route manager basedon desired performance of machines 120 a, 120 b. Alternatively, thethreshold resistance value may be determined based on manufacturerrecommended operating parameters for each of machines 120 a, 120 b, inorder to prolong component life. For example, a manufacturer may specifyparticular operating parameters (e.g., temperature, fluid level, engineoperating speeds and levels, etc.) that must be met in order to maintainthe warranty of the machine. Based on the manufacturer's guidelines,threshold resistance values that keep the machine operating within therecommended performance guidelines may be established. Accordingly,individual machines having actual resistance values that exceed thethreshold resistance value may be flagged for maintenance to diagnose acause of the machine performance.

If on the other hand, the average rolling resistance exceeds thethreshold resistance value (Step 340: Yes), indicating a potentialproblem with the haul route and/or a majority of machines operatingtherein, a proposed haul route modification may be generated (Step 350).According to one embodiment, a user (e.g., subscriber) may createproposed modifications to the haul route and provide these modificationsto performance simulator 160 via input device 148. Alternatively oradditionally, performance simulator 160 may be configured toautomatically generate proposed modifications to the haul route. Forexample, performance simulator 160 may be configured to generate,depending upon how much the average rolling resistance for a particularhaul route segment exceeds the threshold level, a recommended reductionto the grade of the haul route segment to reduce the average rollingresistance of the segment.

Proposed haul route modifications may include any suitable modificationto the haul road surface. For example, haul road modifications mayinclude changes or repairs to the grade of the haul road surface;changes to the haul route density or surface friction by the addition orremoval of certain materials (e.g., concrete, gravel, asphalt, etc.);repairs to potholes, cracks, or other deformities to the haul routesurface; changes to the haul route length or design speed, or any othermodification to the haul route surface that may improve machineperformance over the haul route.

Once haul route modifications have been generated, performance-basedmodels associated with one or more machines may be simulated withrespect to the proposed modifications (Step 360). As explained,performance-based models associated with a machine may be created basedon actual performance data collected from the machine. Performancesimulator 160 may simulate the performance-based model using theproposed haul route modifications. By electronically simulating andanalyzing the proposed modifications prior to making any actual changes,subscribers 170 and/or project managers may be provided with predictionsof the potential impact of the proposed modifications on machine and/orhaul route performance.

Once machine performance corresponding to proposed modifications to thehaul route has been simulated, performance simulator 160 may output thesimulation results (Step 370). For example, performance simulator 160may output the simulation results on display 147 of haul routemanagement system 135. Alternatively or additionally, performancesimulator 160 may generate a haul route modification report 165,identifying one or more problematic haul road segments. Haul routemodification report 165 may include rolling resistance and/or otherperformance statistics (e.g., fuel consumption, greenhouse gas emissionlevel, drive train expected lifespan, etc.) corresponding with theproblematic segments. Haul route modification report 165 may alsoinclude one or more recommendations for improving performance of one ormore machines and/or work environment 100, as well as simulatedperformance data corresponding with the recommendations.

It is contemplated that additional and/or different machine operatingparameters may be used to identify irregular or deficient haul roadconditions. For example, in addition to monitoring trends in rollingresistance to identify potential problems associated with haul roadsegments, performance simulator 160 may identify irregular haul roadsurface conditions by identifying transmission shift patterns associatedwith each of machines 120 a, 120 b. Because each type of machine isdesigned to be most efficient at moderate engine and transmissionoperating zones, it may be advantageous to ensure that the haul routeconditions are conducive for allowing machines to operate at theseefficient operating levels. Thus, if a particular machine is mostefficient operating at 1750 RPMs in second gear, haul road conditionscausing the machine to perform an excessive number of gear shift mayreduce machine efficiency and/or productivity. FIG. 4 provides aflowchart 400 depicting an exemplary method for improving haul roadsurface conditions based on the number of gear shifts performed bymachines operating on the haul route.

As illustrated in FIG. 4, condition monitoring system 140 mayreceive/collect machine performance data from at least one machine (Step410). For example, condition monitoring system 140 of haul routemanagement system 135 may receive/collect performance data from eachmachine operating in work environment 100. According to one embodiment,condition monitoring system 140 may automatically receive this data fromdata collectors 125 associated with each of machines 120 a, 120 b.Alternatively or additionally, condition monitoring system 140 mayprovide a data request to each of machines 120 a, 120 b and receiveperformance data from each machine in response to the request.

Based on the performance data, condition monitoring system 140 maydetermine the number of gear changes associated with each of the atleast one machine and record the number, time, and location of each gearchange in memory (Step 420). For example, condition monitoring system140 may count the number of gear changes for each of machines 120 a, 120b based on transmission and/or engine data received from machines 120 a,120 b. For each gear change, condition monitoring system may record thetime that the gear change occurred, as well as GPS data (e.g., locationand elevation data) corresponding with the gear change. By monitoringthe location of each gear change, performance simulator 160 may be ableto determine the number of gear changes that occurred over a particularhaul route segment.

Performance simulator 160 may determine an average number of gearchanges associated with a particular haul route segment based on thegear change data associated with one or more machines 120 a, 120 b (Step430). Performance simulator 160 may compare the average number of gearchanges associated with a particular haul route segment with a thresholdlimit (Step 440). The threshold limit corresponding with the averagenumber of gear changes may be established based on test data gathered byoperating a healthy machine on the haul route under normal payload andoperating conditions. In some cases, a buffer may be added to the numberof gear changes monitored on the test run to take into account fordriver shift error, payload variations, etc. Thus, if the test dataindicates that 4 gear changes should occur for a particular haul routesegment, the threshold gear change limit may be established as 5 gearchanges (i.e., the 4 gear changes from the test data, plus 1 buffer gearchange to account for operator or machine shift error.)

If the average number of gear changes does not exceed a threshold limit(Step 440: No), indicating that the machines are not experiencingexcessive gear shift due to haul road conditions, the process mayproceed to Step 410 to continue monitoring performance of machines 120a, 120 b. If, on the other hand, the average number of gear changesexceeds a threshold limit, a proposed haul route modification may begenerated (Step 450). According to one embodiment, a user (e.g.,subscriber) may create proposed modifications to the haul route andprovide these modifications to performance simulator 160 via inputdevice 148. Alternatively or additionally, performance simulator 160 maybe configured to automatically generate proposed modifications to thehaul route. For example, performance simulator 160 may be configured togenerate a recommended change to the grade of the haul route segment toreduce the average number of gear changes of machines operating on thesegment. As explained above with respect to FIG. 3, proposed haul routemodifications may include modifications any suitable modification to thehaul road surface.

Once haul route modifications have been generated, performance-basedmodels associated with one or more machines may be simulated withrespect to the proposed modifications (Step 460). As explained,performance-based models associated with a machine may be created basedon actual performance data collected from the machine. Performancesimulator 160 may simulate the performance-based model using theproposed haul route modifications. By electronically simulating andanalyzing the proposed modifications prior to making any actual changes,subscribers 170 and/or project managers may be provided with predictionsof the potential impact of the proposed modifications on machine and/orhaul route performance.

Once machine performance corresponding to proposed modifications to thehaul route has been simulated, performance simulator 160 may output thesimulation results (Step 470). For example, performance simulator 160may output the simulation results on display 147 of haul routemanagement system 135. Alternatively or additionally, performancesimulator 160 may generate a haul route modification report 165,identifying one or more problematic haul road segments. Haul routemodification report 165 may include rolling resistance and/or otherperformance statistics (e.g., fuel consumption, greenhouse gas emissionlevel, drive train expected lifespan, etc.) corresponding with theproblematic segments. Haul route modification report 165 may alsoinclude one or more recommendations for improving performance of one ormore machines and/or work environment 100, as well as simulatedperformance data corresponding with the recommendations.

According to one embodiment, an estimate of the implementation costassociated with the proposed modification(s) may be compiled (Step 480).This estimate may be based on the scope and magnitude of the proposedrecommendations, as well as historical cost data associated with similarhaul route improvement projects. This cost estimate may be provided toperformance simulator 160, which may update/generate a haul routemodification report 165 that includes cost estimate data associated withthe proposed modification(s).

Once machine performance corresponding to proposed modifications to thehaul route has been simulated and costs associated with theimplementation of the proposed modifications have been estimated,performance simulator 160 may output the simulation results (Step 490).As noted above, haul route modification report 165 may include gearchange and/or other performance statistics (e.g., rolling resistance,fuel consumption, greenhouse gas emission level, drive train expectedlifespan, etc.) corresponding with the problematic segment(s). Haulroute modification report 165 may also include one or morerecommendations for improving performance of one or more machines and/orwork environment 100, as well as simulated performance datacorresponding with the recommendations and cost estimates associatedwith implementation of the recommendations.

Although the systems and methods associated with the disclosedembodiments have been described primarily in connection with haul roadsfor mine and construction environments, it is contemplated that thesystems and methods described herein may be applicable to any roadwaysurface. For example, the systems and methods described herein may beemployed on conventional interstate highways and other paved surfaces toidentify changes and irregularities that may be associated withpremature wear, which may result in decreased performance of machines orvehicles operated on these surfaces.

By way of example, the systems and methods described above may beemployed during the construction of a paved highway. During grading andplacement of one or more layers of a new road, one or more “test runs”of vehicles equipped with haul road management system 135 may beoperated on the haul road to identify any irregularities in the roadwaysurface. By detecting irregularities early in the construction phase,these irregularities may be corrected in order to minimize or eliminatethe effects that these types of irregularities have on the performanceof machines to be operated on the haul road.

INDUSTRIAL APPLICABILITY

Methods and systems associated with the disclosed embodiments provide asolution for identifying problems associated with the haul roadconditions based on machine performance data collected during real-timeoperations of the machine on the haul road. The systems and methodsdescribed herein may also allow users to test proposed haul roadmodifications by simulating performance-based machine models todetermine the effectiveness of the proposed modification on theperformance of the machine(s). Work environments that employ theprocesses and features described herein may provide a system thatenables subscribers to effectively identify irregular haul road segmentsand simulate performance of one or more machines based on proposedmodifications to the irregular segments. As a result, subscribers mayselect from a plurality of haul road modification options, based on thedesired performance, productivity, and cost goals of the haul route.

Although the disclosed embodiments are described in relation toimproving haul road conditions in mine environments, they may beapplicable to any environment where it may be advantageous toautomatically detect haul road deficiencies based on machine performancedata and analyze potential haul road improvement options for correctingthese deficiencies. According to one embodiment, the presently disclosedsystem and method for improving haul road conditions may be implementedas part of a connected worksite environment that monitors performancedata associated with a machine fleet and diagnoses potential problemswith machines in the fleet. As a result, systems and methods describedherein may provide an integrated solution for monitoring both machineand haul road health and productivity, in a single integrated system.

The presently disclosed system and method for improving haul roadconditions may have several advantages. For example, the systems andmethods described herein may provide a solution for identifying haulroad deficiencies, propose options for remedying these deficiencies, andanalyze each of the proposed options to identify the costs and benefitsthat each option has on the performance, health, and productivity of themachines and/or the haul road. As a result, mine operators and workenvironment managers may be better equipped to quickly and objectivelydetermine which haul road improvement option is consistent with thelong-term productivity, health, budgetary, and performance goals of thehaul road.

In addition, the presently disclosed haul road improvement system mayhave significant cost advantages. For example, by simulating one or moreproposed options for remedying haul road deficiencies, the presentlydisclosed system enables users to incrementally test certain haul roadimproving options before any actual improvement costs are expended. As aresult, costs and productivity losses due to trail-and-error haul roadimprovement methods may be reduced.

It will be apparent to those skilled in the art that variousmodifications and variations can be made to the disclosed system andmethods for improving haul road conditions without departing from thescope of the invention. Other embodiments of the present disclosure willbe apparent to those skilled in the art from consideration of thespecification and practice of the present disclosure. It is intendedthat the specification and examples be considered as exemplary only,with a true scope of the present disclosure being indicated by thefollowing claims and their equivalents.

1. A method for improving haul road surface conditions comprising:collecting performance data associated with at least one machineoperating on a haul route; determining a rolling resistance of each ofthe at least one machine based on the performance data; determining anaverage rolling resistance based on the rolling resistance of each ofthe at least one machine; identifying a portion of the haul route asirregular if the average rolling resistance of the at least one machineexceeds a threshold resistance value; generating a proposed modificationto the irregular portion of the haul route; simulating a performance ofthe at least one machine based on the proposed modification; andoutputting results of the simulated performance.
 2. The method of claim1, further including estimating a cost associated with implementing theproposed modification based on historical haul route data.
 3. The methodof claim 2, wherein outputting results of the simulated performanceincludes generating a haul route modification report that summarizes oneor more of the proposed modification, results of the simulatedperformance, and the estimated cost associated with implementing theproposed modifications.
 4. The method of claim 1, wherein the proposedmodification includes adjusting an actual grade associated with theirregular portion of the haul route.
 5. The method of claim 1, whereinthe proposed modification includes modifying a surface compositionassociated with the irregular portion of the haul route.
 6. The methodof claim 1, wherein the proposed modification includes modifying asurface density associated with the irregular portion of the haul route.7. The method of claim 1, wherein collecting performance data includescollecting drive axle torque and GPS data associated with the at leastone machine.
 8. The method of claim 5, wherein determining the rollingresistance of each of the at least one machine includes: calculating atotal effective grade associated with the machine based on the driveaxle torque; estimating an actual grade associated with the at least onemachine based on the GPS data; and calculating the rolling resistance ofeach of the at least one machine based on the total effective grade andactual grade associated with the at least one machine.
 9. Acomputer-implemented method for improving haul road surface conditionscomprising: collecting, at a processor associated with a computersystem, performance data associated with at least one machine operatingon a haul route; determining, by the processor, a number of gear changesof each of the at least one machine based on the performance data;determining, by the processor, an average number of gear changes basedon the number of gear changes for each of the at least one machine;identifying, by the processor, one or more portions of the haul route asirregular if the average number of gear changes exceeds a thresholdlimit; and generating, by the processor, a report identifying the one ormore irregular portions of the haul route.
 10. The computer-implementedmethod of claim 9, further including: generating a proposed modificationto one or more irregular portions of the haul route; simulating aperformance of the at least one machine based on the proposedmodification; and outputting results of the simulated performance. 11.The computer-implemented method of claim 10, further includingestimating a cost associated with implementing the proposed modificationbased on historical haul route data.
 12. The computer-implemented methodof claim 11, wherein outputting results of the simulated performanceincludes generating a haul route modification report that summarizes oneor more of the proposed modification, results of the simulatedperformance of the at least one machine, and the estimated costsassociated with implementing the proposed modifications.
 13. Thecomputer-implemented method of claim 10, wherein the proposedmodification includes adjusting an actual grade associated with theirregular portion of the haul route.
 14. The computer-implemented methodof claim 10, wherein the proposed modification includes modifying asurface composition associated with the irregular portion of the haulroute.
 15. The computer-implemented method of claim 10, wherein theproposed modification includes modifying a surface density associatedwith the irregular portion of the haul route.
 16. (canceled) 17.(canceled)
 18. (canceled)
 19. (canceled)
 20. (canceled)
 21. (canceled)22. (canceled)
 23. A computer-implemented method for improving haul roadsurface conditions comprising: collecting, at a processor associatedwith a computer system, performance data associated with at least onemachine operating on a haul route; monitoring, by the processor, atransmission shift pattern associated with the at least one machine;determining, by the processor, whether the monitored transmission shiftpattern conforms to a predetermined shift pattern; identifying, by theprocessor, one or more portions of the haul route as irregular if thetransmission shift pattern does not conform to the predetermined shiftpattern; generating, by the processor, a proposed modification to one ormore irregular portions of the haul route; simulating, by the processor,a performance of the at least one machine based on the proposedmodification; and outputting results of the simulated performance. 24.The computer-implemented method of claim 23, further includingestimating a cost associated with implementing the proposed modificationbased on historical haul route data, wherein outputting results of thesimulated performance includes generating a haul route modificationreport that summarizes one or more of the proposed modification, resultsof the simulated performance of the at least one machine, and theestimated costs associated with implementing the proposed modifications.25. The computer-implemented method of claim 23, wherein the proposedmodification includes adjusting an actual grade associated with theirregular portion of the haul route.
 26. The computer-implemented methodof claim 23, wherein the proposed modification includes modifying asurface composition associated with the irregular portion of the haulroute.
 27. The computer-implemented method of claim 23, wherein theproposed modification includes modifying a surface density associatedwith the irregular portion of the haul route.